Open Science Research Excellence

Open Science Index

Commenced in January 2007 Frequency: Monthly Edition: International Publications Count: 31097

Select areas to restrict search in scientific publication database:
Road Vehicle Recognition Using Magnetic Sensing Feature Extraction and Classification
This paper presents a road vehicle detection approach for the intelligent transportation system. This approach mainly uses low-cost magnetic sensor and associated data collection system to collect magnetic signals. This system can measure the magnetic field changing, and it also can detect and count vehicles. We extend Mel Frequency Cepstral Coefficients to analyze vehicle magnetic signals. Vehicle type features are extracted using representation of cepstrum, frame energy, and gap cepstrum of magnetic signals. We design a 2-dimensional map algorithm using Vector Quantization to classify vehicle magnetic features to four typical types of vehicles in Australian suburbs: sedan, VAN, truck, and bus. Experiments results show that our approach achieves a high level of accuracy for vehicle detection and classification.
Digital Object Identifier (DOI):


[1] US Department of Transportation (2006) “Federal Highway Administration Research and Technology Coordinating, Developing Highway Transportation Innovations” May 2006.
[2] Mazarakis Georgios and Avaritsiotis (2007) “Vehicle classification in sensor networks using time-domain signal processing and neural networks”, Microprocessors and MICROSYSTEMS, Vol 31. pp 381-392, Feb. 2007.
[3] Shi, Shengli, Zhong Qin, and Jianmin Xu (2007) “Robust algorithm of vehicle classification”, Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2007. SNPD 2007. Eighth ACIS International Conference on. Vol. 3. IEEE, 2007.
[4] Caruso, Michael J., and Lucky S. Withanawasam. (1999) “Vehicle detection and compass applications using AMR magnetic sensors”, Sensors Expo Proceedings. Vol. 477. 1999.
[5] Chou, Hsi-Tseng & Tuan, Shih-Chung & Ho, Hsien-Kwei. (2016). “Numerical estimation of electromagnetic backscattering from near-zone vehicles for the side-look vehicle-detection radar applications at millimeter waves”, IEEE, 129-133. 10.1109.
[6] Ignacio Llamas-Garro, Konstantin Lukin, Marcos T. de Melo; Jung-Mu Kim, (2016) “Frequency and angular estimation of detected microwave source using aerial vehicles”, 2016 IEEE MTT-S Latin America Microwave Conference (LAMC), Poerto Vallarta, Mexico.
[7] Gajda J. and Stencel M. (2014) “A highly selective vehicle classification utilizing dual-loop inductive detector”, Metrology and measurement systems, 2014, 21 (3), pp 473-484.
[8] Chen, H.-T & Chu, M.-C & Chou, C.-L & Lee, S.-Y & Lin, B.-S. (2015). “Multi-camera vehicle identification in tunnel surveillance system”, IEEE. 10.1109.
[9] Jihyuck Jo, Hoyoung Yoo, and In-Cheol Park (2016) “Energy-Efficient Floating-Point MFCC Extraction Architecture for Speech Recognition Systems “, IEEE Trans (VLSI), Vol. 24, No. 2, March 2016.
[10] Michael Pitz, Ralf Schl¨uter, and Hermann Ney Sirko Molau (2001) "Computing Mel-Frequency Cepstral Coefficients on the Power Spectrum," in 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01), USA, 2001, pp. 73-76.
[11] A. B. Kandali, A. Routray, and T. K. Basu, (2008) “Emotion recognition from assamese speeches using mfcc features and gmm classifier,” in TENCON 2008-2008 IEEE Region 10 Conference. IEEE, 2008, pp. 1–5.
[12] T. F. Quatieri (2002) Discrete-time speech signal processing: principles and practice. Pearson Education India, 2002.
[13] S. Singh, and E. Rajan (2011) “Vector Quantization approach for speaker recognition using MFCC and inverted MFCC”, International Journal of Computer Applications, Vol. 17, No. 1, Mar 2011.
[14] Gray, Robert. (1984) "Vector quantization." IEEE ASSP Magazine 1.2 (1984): 4-29.
Vol:15 No:02 2021Vol:15 No:01 2021
Vol:14 No:12 2020Vol:14 No:11 2020Vol:14 No:10 2020Vol:14 No:09 2020Vol:14 No:08 2020Vol:14 No:07 2020Vol:14 No:06 2020Vol:14 No:05 2020Vol:14 No:04 2020Vol:14 No:03 2020Vol:14 No:02 2020Vol:14 No:01 2020
Vol:13 No:12 2019Vol:13 No:11 2019Vol:13 No:10 2019Vol:13 No:09 2019Vol:13 No:08 2019Vol:13 No:07 2019Vol:13 No:06 2019Vol:13 No:05 2019Vol:13 No:04 2019Vol:13 No:03 2019Vol:13 No:02 2019Vol:13 No:01 2019
Vol:12 No:12 2018Vol:12 No:11 2018Vol:12 No:10 2018Vol:12 No:09 2018Vol:12 No:08 2018Vol:12 No:07 2018Vol:12 No:06 2018Vol:12 No:05 2018Vol:12 No:04 2018Vol:12 No:03 2018Vol:12 No:02 2018Vol:12 No:01 2018
Vol:11 No:12 2017Vol:11 No:11 2017Vol:11 No:10 2017Vol:11 No:09 2017Vol:11 No:08 2017Vol:11 No:07 2017Vol:11 No:06 2017Vol:11 No:05 2017Vol:11 No:04 2017Vol:11 No:03 2017Vol:11 No:02 2017Vol:11 No:01 2017
Vol:10 No:12 2016Vol:10 No:11 2016Vol:10 No:10 2016Vol:10 No:09 2016Vol:10 No:08 2016Vol:10 No:07 2016Vol:10 No:06 2016Vol:10 No:05 2016Vol:10 No:04 2016Vol:10 No:03 2016Vol:10 No:02 2016Vol:10 No:01 2016
Vol:9 No:12 2015Vol:9 No:11 2015Vol:9 No:10 2015Vol:9 No:09 2015Vol:9 No:08 2015Vol:9 No:07 2015Vol:9 No:06 2015Vol:9 No:05 2015Vol:9 No:04 2015Vol:9 No:03 2015Vol:9 No:02 2015Vol:9 No:01 2015
Vol:8 No:12 2014Vol:8 No:11 2014Vol:8 No:10 2014Vol:8 No:09 2014Vol:8 No:08 2014Vol:8 No:07 2014Vol:8 No:06 2014Vol:8 No:05 2014Vol:8 No:04 2014Vol:8 No:03 2014Vol:8 No:02 2014Vol:8 No:01 2014
Vol:7 No:12 2013Vol:7 No:11 2013Vol:7 No:10 2013Vol:7 No:09 2013Vol:7 No:08 2013Vol:7 No:07 2013Vol:7 No:06 2013Vol:7 No:05 2013Vol:7 No:04 2013Vol:7 No:03 2013Vol:7 No:02 2013Vol:7 No:01 2013
Vol:6 No:12 2012Vol:6 No:11 2012Vol:6 No:10 2012Vol:6 No:09 2012Vol:6 No:08 2012Vol:6 No:07 2012Vol:6 No:06 2012Vol:6 No:05 2012Vol:6 No:04 2012Vol:6 No:03 2012Vol:6 No:02 2012Vol:6 No:01 2012
Vol:5 No:12 2011Vol:5 No:11 2011Vol:5 No:10 2011Vol:5 No:09 2011Vol:5 No:08 2011Vol:5 No:07 2011Vol:5 No:06 2011Vol:5 No:05 2011Vol:5 No:04 2011Vol:5 No:03 2011Vol:5 No:02 2011Vol:5 No:01 2011
Vol:4 No:12 2010Vol:4 No:11 2010Vol:4 No:10 2010Vol:4 No:09 2010Vol:4 No:08 2010Vol:4 No:07 2010Vol:4 No:06 2010Vol:4 No:05 2010Vol:4 No:04 2010Vol:4 No:03 2010Vol:4 No:02 2010Vol:4 No:01 2010
Vol:3 No:12 2009Vol:3 No:11 2009Vol:3 No:10 2009Vol:3 No:09 2009Vol:3 No:08 2009Vol:3 No:07 2009Vol:3 No:06 2009Vol:3 No:05 2009Vol:3 No:04 2009Vol:3 No:03 2009Vol:3 No:02 2009Vol:3 No:01 2009
Vol:2 No:12 2008Vol:2 No:11 2008Vol:2 No:10 2008Vol:2 No:09 2008Vol:2 No:08 2008Vol:2 No:07 2008Vol:2 No:06 2008Vol:2 No:05 2008Vol:2 No:04 2008Vol:2 No:03 2008Vol:2 No:02 2008Vol:2 No:01 2008
Vol:1 No:12 2007Vol:1 No:11 2007Vol:1 No:10 2007Vol:1 No:09 2007Vol:1 No:08 2007Vol:1 No:07 2007Vol:1 No:06 2007Vol:1 No:05 2007Vol:1 No:04 2007Vol:1 No:03 2007Vol:1 No:02 2007Vol:1 No:01 2007